A 12-nm Autonomous Driving Processor With 60.4 TOPS, 13.8 TOPS/W CNN Executed by Task-Separated ASIL D Control Katsushige Matsubara , Hanno Lieske , Motoki Kimura, Atsushi Nakamura, Manabu Koike, Shun Morikawa

Abstract

This article proposes an automotive safety integrity level (ASIL) D, which is the highest automotive integrity level specified in ISO 26262, and a target application processor for driving automation systems with a high convolutional neural network (CNN) processing performance of 60.4 trillion operations per second (TOPS) with high power efficiency of 13.8 TOPS/W. To achieve both performance and power efficiency, a stream processing architecture specialized for CNN hardware module is adopted to implement many low-power arithmetic units. In addi- tion, 6 MB of local memories are implemented to reduce data transfers between dynamic random access memory (DRAM) and the CNN hardware, thereby improving the execution efficiency of the arithmetic units and saving power consumption caused by the data transfer. In order to support high safety integrity level with power efficiency, we provide safety mechanisms with high failure detection rates only for the hardware used in applications that require ASIL D support. The configuration of two CNN modules can switch between lockstep and single operation depending on the use case, thus achieving a tradeoff between performance and ASIL while maintaining power efficiency. In addition, the freedom from interference (FFI) concept defined in ISO 26262 is achieved by providing mechanisms to prevent low safety level tasks from interfering with high safety level tasks running concurrently inside the processor.